基于ArcView-WOE的下辽河平原地下水生态系统健康评价

地下水生态系统是生态系统的重要类型,随着社会经济的发展,地下水资源与环境压力日益增大,地下水生态系统健康问题已经成为人类重点关注的环境问题之一。以ArcView为平台,以下辽河平原硝酸盐氮浓度为响应因子,并从地下水系统结构特征、区域自然条件、外界压力、资源与保护和生态环境5个方面建立证据因子的图层数据库,利用证据权重法(WOE)对下辽河平原地下水生态系统健康进行评价,得到硝酸盐氮后验概率分布图。结果表明:下辽河平原的西北、东北部、东南部及抚顺和辽阳地区地下水生态系统健康处于相对高和较高概率区,东部山前冲洪积平原及下辽河平原的周边地区处于中等概率区,下辽河平原的中部平原、南部滨海平原地区处于相对低和较低概率区。将地下水水质监测点硝酸盐氮含量与后验概率分布图进行对比分析,发现二者对应性较好,这说明WOE可以用于地下水生态系统健康评价,其概率表现形式能够有效的弥补传统生态系统健康评价结果是一个具体值(或等级)而无法反映生态系统健康不确定性的不足。

Ecological health assessment of groundwater in the lower Liaohe River Plain using an ArcView-WOE technique

Groundwater is an important part of the worldwide ecosystem, and is also a core part of the global water cycle. Groundwater is a key influence on the ecological system in arid and semi-arid regions of northwest China, and is the primary source of water for human use in northern China. With recent economic growth, rapid development of the groundwater resources in this region is occurring. The groundwater has been and is being seriously depleted and some unhealthy characteristics and vulnerabilities in the system, which are significantly impacting the ecology of the area, are becoming apparent. The ecological health of groundwater systems has become a serious issue in ecology, and is receiving considerable attention from the general public. An ecological health assessment of a groundwater system can be used to facilitate the protection of the environment and encourage sustainable development of groundwater resources. This paper provides a case study in the lower Liaohe River alluvial plain, which is in the most economically developed region of Liaoning Province. The area is experiencing significant water shortages. Ten evidence factors were identified to describe the attributes of the ecological health of the groundwater system. These evidence factors were based on five aspects of the groundwater system including:(1) characteristics of the local groundwater system; (2) natural conditions in the region; (3) external pressures including human-induced pressures; (4) available resources and conservation; and (5) the local ecological environment. The nitrate concentration in fifty-three groundwater monitoring wells in the study area was used as the response, because the nitrate concentration is a typical indicator of groundwater pollution. In this paper we took used the ArcView GIS software as the assessment platform, and used the weights of evidence (WOE) method to assess the ecological health of the groundwater system in the lower Liaohe River plain. A posteriori probability map of the nitrate concentration was generated, and the probabilities were divided into five categories, defined as (1) low probability; (2) moderately low probability; (3) moderate probability; (4) moderately high probability; and (5) high probability, with probability ranges of 0.000-0.005, 0.005-0.015, 0.015-0.233, 0.233-0.490 and 0.490-0.832, respectively. The result indicate that high and moderately high probability regions include the northwest, northeast and southeast of the lower Liaohe River plain, as well as Liaoyang and Fushun cities. The eastern alluvial floodplain and its surroundings belong to the moderate probability region; and the low and moderately low probability regions include the middle and southern coastal plain areas. The proportions of the study area in each probability category are:34.02% low probability; 23.81% moderately low probability; 34.31% moderate probability; 3.81% moderately high probability; and, 4.05% high probability. A comparison analysis between the posteriori probability map of nitrate concentrations and the measured concentrations in monitoring wells found a very good correlation. This indicates that the assessment results are valid, and the WOE method can be successfully applied to assess the ecological health of a groundwater system. Further, the results of the WOE method are probabilities, while traditional ecological health assessment methods provide a determined value (or degree), which does not accurately reflect the stochastic characteristics of ecological system health. The WOE method provides a more accurate reflection of ecological health.